Вода і водоочисні технології. Науково-технічні вісті, № 3(37)

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Перегляд Вода і водоочисні технології. Науково-технічні вісті, № 3(37) за Автор "Orestov, Yevhen"

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    Digitalization of water vending machines
    (КПІ ім. Ігоря Сікорського; ТОВ «Українська водна спілка», 2023) Mudryk, Rostyslav; Orestov, Yevhen
    Vending, the sale of goods and services through automated systems, has gained worldwide popularity as a convenient and low-maintenance method of commerce or service delivery. With its wide range of applications, vending can be used in almost all areas of commercial and social life. This article is dedicated to studying the impact of digitalization on the operation of water vending machines. These machines represent a modern way of obtaining safe and physiologically complete drinking water. Their advantage lies in autonomous operation without the constant presence of servicing personnel. This is achieved by replacing filters and maintenance tasks carried out on a time-based logic basis. However, time-based logic does not account for actual volumes of purified water, leading to over expenditure on servicing some machines and untimely maintenance, resulting in a deterioration of water quality for others. This study investigates the impact of digitalization on optimizing service costs and the cost price of water purification. It is shown that through digitalization, the maintenance logic was changed to volume-based, resulting in reduced expenses on replacement filters (51%), servicing (13%), and collection (17%). Collectively, these factors reduced the cost of water by 20%. The decrease in cost enhances the profitability of the vending machine network. With a fixed water price, this is the only way to increase profitability and attract investors, consequently popularizing water vending machines. Subsequent research will focus on seeking alternative filters, materials, and water preparation technologies to achieve even greater machine autonomy. By assessing the established impact of digitalization on water vending machine operations, a predictive cost of water is calculated, assuming compliance with all operational requirements. The predicted cost reduction amounts to 39%, providing economic justification for future research endeavors.